An Introduction to Statistical Methods and Data Analysis
7th Edition
ISBN: 9781305269477
Author: R. Lyman Ott, Micheal T. Longnecker
Publisher: Cengage Learning
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Suppose a study wants to predict the market price of a certain species of turtle (Y) based on the following independent variables indicated in the table. Based from the table, what is the equation of the multiple linear regression? (Round off up to two decimal places.Â
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Market Price = 0.07 - 0.40*weight + 1.51*length + 1.41*width + 0.80*age
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Market Price = 0.07 + 0.40*weight + 1.51*length + 1.41*width + 0.80*age
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Market Price = 0.07 - 0.40 + weight + 1.51 + length + 1.41 + width + 0.80 + age
A researcher notes​ that, in a certain​ region, a disproportionate number of software millionaires were born around the year 1955. Is this a​ coincidence, or does birth year matter when gauging whether a software founder will be​successful? The researcher investigated this question by analyzing the data shown in the accompanying table. Complete parts a through c below.
a. Find the coefficient of determination for the simple linear regression model relating number​ (y) of software millionaire birthdays in a decade to total number​ (x) of births in the region. Interpret the result.
The coefficient of determination is 1.___?
​(Round to three decimal places as​ needed.)
This value indicates that 2.____Â of the sample variation in the number of software millionaire birthdays is explained by the
linear relationship with the total number of births in the region.
​(Round to one decimal place as​ needed.)
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b. Find the coefficient of determination for the simple linear regression model…
A sixth-grade teacher believes that there is a relationship between his students’ IQscores (y) and the numbers of hours (x) they spend watching television each week. Thefollowing table shows a random sample of 7 sixth-grade students.y 125 116 97 114 85 107 105x 5 10 30 16 41 28 21
Does the data provide sufficient evidence to indicate that the simple linear regressionmodel is appropriate to describe the relationship between x and y? Perform a model utilitytest at α = 0.05. (Give H0, Ha, rejection region, observed test statistic, P-value, decisionand conclusion.)Find the Pearson sample correlation coefficient between x and y. Then interpretthe result.
Chapter 11 Solutions
An Introduction to Statistical Methods and Data Analysis
Ch. 11.9 - Prob. 1ECh. 11.9 - Refer to Exercise 11.1.
Plot the equation in the...Ch. 11.9 - Use the data given here to answer the following...Ch. 11.9 - Prob. 4ECh. 11.9 - Use the output from Minitab for these data to...Ch. 11.9 - A food processor was receiving complaints from its...Ch. 11.9 - An online retailer needs to manage the amount of...Ch. 11.9 - A manufacturer of cases for sound equipment...Ch. 11.9 - Refer to the data of Exercise 11.7. a. Calculate a...Ch. 11.9 - Refer to the data of Exercise 11.8.
Calculate a...
Ch. 11.9 - Refer to the data of Exercise 11.8.
Calculate a...Ch. 11.9 - Athletes are constantly seeking measures of the...Ch. 11.9 - A firm that prints automobile bumper stickers...Ch. 11.9 - A chemist is interested in determining the weight...Ch. 11.9 - Refer to Exercise 11.22 to complete the following....Ch. 11.9 - Prob. 40ECh. 11.9 - A survey of MBA, graduates of a business school...Ch. 11.9 - Refer to the data in Exercise 11.44.
Determine the...Ch. 11.9 - There has been an increasing emphasis in recent...Ch. 11.9 - An air conditioning company responds to calls...Ch. 11.9 - Refer to Exercise 11.61. a. Calculate the...Ch. 11.9 - Refer to Exercise 11.61.
Test for lack of fit for...Ch. 11.9 - Refer to Exercise 11.61.
Compute the standard...Ch. 11.9 - Prob. 93SE
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardThe following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardThe following are data on the average weekly profits(in $1,000) of five restaurants, their seating capacities, andthe average daily traffic (in thousands of cars) that passestheir locations: Seating Traffic Weekly netcapacity count profitx1 x2 y120 19 23.8200 8 24.2150 12 22.0180 15 26.2240 16 33.5 (a) Assuming that the regression is linear, estimate β0, β1,and β2.(b) Use the results of part (a) to predict the averageweekly net profit of a restaurant with a seating capacityof 210 at a location where the daily traffic count averages14,000 cars.arrow_forward
- If we collect monthly sales over two years for N=100 stores, we should not apply a simple linear regression model directly to the data, because the observations are not independent with each other. Is this statement True or False? A) True B) Falsearrow_forwardIn order to determine a realistic price for a new product that a company wants to market the company’s research department selected 10 sites thought to have essentially identical sales potential and offered the product in each at a different price. The resulting sales are recorded in the accompanying table:  Price ($) Sales ($1,000s) 15.00 15 15.50 14 16.00 16 16.50 9 17.00 12 17.50 10 18.00 8 18.50 9 19.00 6 19.50 5 h). Estimate the slope of the actual equation of the regression line using a 95% confidence interval and interpret this interval.arrow_forwardIn order to determine a realistic price for a new product that a company wants to market the company’s research department selected 10 sites thought to have essentially identical sales potential and offered the product in each at a different price. The resulting sales are recorded in the accompanying table:  Price ($) Sales ($1,000s) 15.00 15 15.50 14 16.00 16 16.50 9 17.00 12 17.50 10 18.00 8 18.50 9 19.00 6 19.50 5 h). Estimate the slope of the actual equation of the regression line using a 95% confidence interval and interpret this interval using Minitab.arrow_forward
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